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On Seemingly Unrelated Regressions with Linear Restrictions

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  • Lichun Wang

    (Department of Mathematics, Beijing Jiaotong University, China)

Abstract

The paper shows that, in the system of two seemingly unrelated regressions with linear restrictions, there are two methods can be used to obtain the best restricted least square estimator for the parameter of interest which involves a matrix power series, and thus conclude the best restricted least-square estimator only has unique simpler form.

Suggested Citation

  • Lichun Wang, 2018. "On Seemingly Unrelated Regressions with Linear Restrictions," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 6(4), pages 110-113, April.
    • Handle: RePEc:adp:jbboaj:v:6:y:2018:i:4:p:110-113
    DOI: 10.19080/BBOAJ.2018.06.555692
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    References listed on IDEAS

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    1. Swamy, P. A. V. B. & Mehta, J. S., 1975. "On Bayesian estimation of seemingly unrelated regressions when some observations are missing," Journal of Econometrics, Elsevier, vol. 3(2), pages 157-169, May.
    2. Bhattacharya, Debopam, 2004. "Seemingly unrelated regressions with identical regressors: a note," Economics Letters, Elsevier, vol. 85(2), pages 247-255, November.
    3. Baksalary, Jerzy K. & Trenkler, Gotz, 1991. "Covariance adjustment in biased estimation," Computational Statistics & Data Analysis, Elsevier, vol. 12(2), pages 221-230, September.
    4. Schmidt, Peter, 1977. "Estimation of seemingly unrelated regressions with unequal numbers of observations," Journal of Econometrics, Elsevier, vol. 5(3), pages 365-377, May.
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